Abstract
Several artificial intelligence methods of short-term electrical load forecasting are discussed in the paper. The model of a hybrid system based on syntactic pattern recognition, neural networks, and fuzzy techniques is introduced. The application of the model and the experimental results of short-term electrical load forecasting are presented.
This work was supported by the Polish State Committee for Scientific Research (KBN) under Grant No. 3 T11C 054 26.
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Jurek, J., Peszek, T. (2005). On the Use of Syntactic Pattern Recognition Methods, Neural Networks, and Fuzzy Systems for Short-Term Electrical Load Forecasting. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_100
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DOI: https://doi.org/10.1007/3-540-32390-2_100
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25054-8
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